APA
In-text citation: (Hurdle et al., 2022)
Reference: Hurdle, Z. B., Akbuga, E., & Schrader, P. (2022). Exploring Calculus I students’ performance between varying course times among other predictive variables.
International Electronic Journal of Mathematics Education, 17(4), em0700.
https://doi.org/10.29333/iejme/12234
AMA
In-text citation: (1), (2), (3), etc.
Reference: Hurdle ZB, Akbuga E, Schrader P. Exploring Calculus I students’ performance between varying course times among other predictive variables.
INT ELECT J MATH ED. 2022;17(4), em0700.
https://doi.org/10.29333/iejme/12234
Chicago
In-text citation: (Hurdle et al., 2022)
Reference: Hurdle, Zachariah Benton, Enes Akbuga, and Paul Schrader. "Exploring Calculus I students’ performance between varying course times among other predictive variables".
International Electronic Journal of Mathematics Education 2022 17 no. 4 (2022): em0700.
https://doi.org/10.29333/iejme/12234
Harvard
In-text citation: (Hurdle et al., 2022)
Reference: Hurdle, Z. B., Akbuga, E., and Schrader, P. (2022). Exploring Calculus I students’ performance between varying course times among other predictive variables.
International Electronic Journal of Mathematics Education, 17(4), em0700.
https://doi.org/10.29333/iejme/12234
MLA
In-text citation: (Hurdle et al., 2022)
Reference: Hurdle, Zachariah Benton et al. "Exploring Calculus I students’ performance between varying course times among other predictive variables".
International Electronic Journal of Mathematics Education, vol. 17, no. 4, 2022, em0700.
https://doi.org/10.29333/iejme/12234
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Hurdle ZB, Akbuga E, Schrader P. Exploring Calculus I students’ performance between varying course times among other predictive variables. INT ELECT J MATH ED. 2022;17(4):em0700.
https://doi.org/10.29333/iejme/12234
Abstract
This study focuses on the analysis of certain performance predictors for calculus I. We collected data from 717 students from 2013 through 2018 at a southeastern university in the United States to explore any correlation between course times (particularly very early versus the rest) and student performance in this specific course, along with a handful of other variables. This represented all calculus I students over this time period. A two-proportion test confirmed that time was a significant variable in performance. We then used regression to determine similar impacts of gender, major, instructor, and term on student performance. Initial findings portrayed statistical differences between terms and course times; other findings included the significance of major and instructor in different contexts. Interaction effects were used with time to complete our analysis of its impact, and controls were later used accordingly. We also display appropriate models for comparing categories. We conclude with some basic assertions and argue some departmental recommendations on how to use these findings in undergraduate mathematics education.